Can the power of mammography to correctly identify breast
cancers be improved used artificial intelligence or machine learning? A recent
study finds it can. William Nelson, director of the Kimmel Cancer Center at
Johns Hopkins, describes the data.

Nelson: This was Google’s play to look at mammography. They
ended up having a dataset of 28,000 mammographic images. The upshot of it was
in the US the false positive rate was reduced from 5.7% to 1.2%, saying that
this looked like it could be breast cancer and it turned out not to be. The
false negative rate which was reduced by 9.4% down to 2.7% which is saying this
doesn’t look like breast cancer even though it was, if you look at the AI tool
it was roughly equivalent to having a second reader. :30

Nelson says images are among the most suitable for
interpretation by artificial intelligence, and he expects that to extend into
other forms of cancer, such as melanoma and other skin cancers. At Johns
Hopkins, I’m Elizabeth Tracey.